restore accumulateFactorMeans

Author: dehann

NEWS.md

@@ -23,7 +23,6 @@ The list below highlights major breaking changes, and please note that significa
 - Deprecate use of `getParametricMeasurement` and use `getMeasurementParametric` instead, and add `<:AbstractManifold` to API.
 - Deprecate use of `solveBinaryFactorParameteric`, instead use `solveFactorParameteric`.
 - Deprecating `approxConvBinary`, use `approxConvBelief` instead.
-- Deprecating `accumulateFactorChain`, use `approxConvBelief` instead.
 
 
 # Major changes in v0.24

src/Deprecated.jl

@@ -26,49 +26,6 @@ end
 ##==============================================================================
 
 
-# """
-#     $SIGNATURES
-
-# Calculate both measured and predicted relative variable values, starting with `from` at zeros up to `to::Symbol`.
-
-# Notes
-# - assume single variable separators only.
-
-# DevNotes
-# - TODO better consolidate with [`approxConvBelief`](@ref) which can now also work with factor chains.
-# """
-# function accumulateFactorChain( dfg::AbstractDFG,
-#                                 from::Symbol,
-#                                 to::Symbol,
-#                                 fsyms::Vector{Symbol}=findFactorsBetweenNaive(dfg, from, to);
-#                                 initval=zeros(size(getVal(dfg, from))))
-
-#   # get associated variables
-#   svars = union(ls.(dfg, fsyms)...)
-
-#   # use subgraph copys to do calculations
-#   tfg_meas = buildSubgraph(dfg, [svars;fsyms])
-#   tfg_pred = buildSubgraph(dfg, [svars;fsyms])
-
-#   # drive variable values manually to ensure no additional stochastics are introduced.
-#   nextvar = from
-#   initManual!(tfg_meas, nextvar, initval)
-#   initManual!(tfg_pred, nextvar, initval)
-
-#   # nextfct = fsyms[1] # for debugging
-#   for nextfct in fsyms
-#     nextvars = setdiff(ls(tfg_meas,nextfct),[nextvar])
-#     @assert length(nextvars) == 1 "accumulateFactorChain requires each factor pair to separated by a single variable"
-#     nextvar = nextvars[1]
-#     meas, pred = approxDeconv(dfg, nextfct) # solveFactorMeasurements
-#     pts_meas = approxConv(tfg_meas, nextfct, nextvar, (meas,ones(Int,100),collect(1:100)))
-#     pts_pred = approxConv(tfg_pred, nextfct, nextvar, (pred,ones(Int,100),collect(1:100)))
-#     initManual!(tfg_meas, nextvar, pts_meas)
-#     initManual!(tfg_pred, nextvar, pts_pred)
-#   end
-#   return getVal(tfg_meas,nextvar), getVal(tfg_pred,nextvar)
-# end
-
 
 # # TODO should this be consolidated with regular approxConv?
 # # TODO, perhaps pass Xi::Vector{DFGVariable} instead?

src/services/ApproxConv.jl

@@ -1,6 +1,6 @@
 
 export calcFactorResidual
-
+export accumulateFactorChain
 
 
 function approxConvBelief(dfg::AbstractDFG,
@@ -299,5 +299,48 @@ end
 
 
 
+"""
+    $SIGNATURES
+
+Calculate both measured and predicted relative variable values, starting with `from` at zeros up to `to::Symbol`.
+
+Notes
+- assume single variable separators only.
+
+DevNotes
+- TODO better consolidate with [`approxConvBelief`](@ref) which can now also work with factor chains.
+"""
+function accumulateFactorChain( dfg::AbstractDFG,
+                                from::Symbol,
+                                to::Symbol,
+                                fsyms::Vector{Symbol}=findFactorsBetweenNaive(dfg, from, to);
+                                initval=zeros(size(getVal(dfg, from))))
+
+  # get associated variables
+  svars = union(ls.(dfg, fsyms)...)
+
+  # use subgraph copys to do calculations
+  tfg_meas = buildSubgraph(dfg, [svars;fsyms])
+  tfg_pred = buildSubgraph(dfg, [svars;fsyms])
+
+  # drive variable values manually to ensure no additional stochastics are introduced.
+  nextvar = from
+  initManual!(tfg_meas, nextvar, initval)
+  initManual!(tfg_pred, nextvar, initval)
+
+  # nextfct = fsyms[1] # for debugging
+  for nextfct in fsyms
+    nextvars = setdiff(ls(tfg_meas,nextfct),[nextvar])
+    @assert length(nextvars) == 1 "accumulateFactorChain requires each factor pair to separated by a single variable"
+    nextvar = nextvars[1]
+    meas, pred = approxDeconv(dfg, nextfct) # solveFactorMeasurements
+    pts_meas = approxConv(tfg_meas, nextfct, nextvar, (meas,ones(Int,100),collect(1:100)))
+    pts_pred = approxConv(tfg_pred, nextfct, nextvar, (pred,ones(Int,100),collect(1:100)))
+    initManual!(tfg_meas, nextvar, pts_meas)
+    initManual!(tfg_pred, nextvar, pts_pred)
+  end
+  return getVal(tfg_meas,nextvar), getVal(tfg_pred,nextvar)
+end
+
 
 #